Method for determining particle characteristics

ABSTRACT

The present invention provides methods and apparatuses for determining at least one of a plurality of particle physical characteristics. The particle physical characteristics include particle size, shape, magnetic susceptibility, magnetic label density, charge separation, dielectric constant, and derivatives thereof. The method includes generating a region of space having a substantially constant force field, determining the velocity of at least one particle within the region by identifying and locating the particle and its coordinates in at least two temporally defined digital images, and determining the particle physical characteristics from the determined velocity and a predetermined force field magnitude and direction. A device for determining one or more particle physical characteristics is described which has a force field device for subjecting at least one particle to at least one force field, a substantially transparent flow channel, and a computer system for gathering and analyzing data associated with the at least one particle. A system for determining one or more particle physical characteristics is provided which has a force field device for generating at least one force field having a predetermined force field magnitude and direction and for subjecting at least one particle to the at least one force field, a flow system for regulating the introduction of the at least one particle into the force field device, and a computer system for gathering and analyzing data associated with the at least one particle. A pole piece assembly for producing a region of space having a substantially constant magnetic force field is also provided.

Federal sponsorship of this invention has been provided by Contract No.CA623349.

RELATED APPLICATIONS

This patent application is related to patent application Ser. No.09/020,327, filed Feb. 6, 1998, titled "System and Device forDetermining Particle Characteristics" which is hereby incorporated byreference.

FIELD OF THE INVENTION

The invention relates generally to methods and apparatuses fordetermining particle characteristics, and more particularly, to methodsand apparatuses having particle tracking and image analysis logic andforce field devices for determining one or more physical cellcharacteristics.

BACKGROUND OF THE INVENTION

Cell analysis and separation is an increasingly important technique inthe diagnosis and treatment of various cancers and diseases. Of primaryimportance to cell analysis and separation is the ability to identify,or label, cell properties and characteristics of interest. Theidentification, or labeling, of cell properties and characteristicsallows them to be used as "handles" which, in turn, can be used toseparate "labeled" cells from other cells. Among the most commonly usedlabels for sorting cells are immunological labels which include, forexample, immunofluorescent and immunomagnetic labels. Immunofluorescentlabels typically include, for example, a fluorescent molecule joined toan antibody. Immunomagnetic labels typically include, for example, aparamagnetic compound or molecule joined to either a primary orsecondary antibody. Cell labeling is performed by attaching the antibodyto a marker of interest on the surface of the cell (i.e., cell surfacemarker).

However, though extremely sensitive immunological "labels" have beendeveloped which allow for the careful labeling of cells, the potentialof these labels for cellular analysis and separation has yet to be fullyrealized. As a result thereof, the cellular properties andcharacteristics which these labels are capable of identifying have alsoyet to be fully analyzed. For example, in the case of immunomagneticlabels, the highly accurate quantification of a cell population'smagnetic susceptibility has been impossible to determine. Additionally,in the general case of immunological labels, the cell surface marker andlabel density has been difficult to accurately determine.

These deficiencies are due, in large part, to the limitations ofanalytical devices which are capable of gathering and analyzing theinformation these immunological labels can provide about cells.Moreover, the lack of qualitative and quantitative knowledge of cellproperties and characteristics, such as magnetic susceptibility and cellsurface marker and label density, hampers the development ofsophisticated cell sorting apparatuses. Accordingly, it is an object ofthe present invention to provide a method and apparatus forqualitatively and quantitatively analyzing one or more cellcharacteristics or properties.

SUMMARY OF THE INVENTION

According to one aspect of the present invention, apparatuses andmethods are provided for quantifying at least one of a plurality ofparticle physical characteristics. The range of particles includes, forexample, cells, cell organelles, platelets, inorganic, organic,biological, and polymeric particles which are optically visible. Theplurality of particle physical characteristics include particle size,shape, magnetic susceptibility, magnetic label density, chargeseparation, dielectric constant, and derivatives thereof. Derivativesinclude, for example, cell dimensions (e.g., diameter, radius, majoraxis length, minor axis length, etc.) and optical transmittance. Themethod includes generating a region of space having a substantiallyconstant force field, determining the velocity of at least one particlewithin the region by identifying and locating the particle and itscoordinates in at least two temporally defined digital images, anddetermining the at least one of a plurality of particle physicalcharacteristics from the determined velocity and a predetermined forcefield magnitude and direction.

These steps include several steps or sub-steps. In particular, the stepof determining the velocity of at least one particle in a force fieldincludes the step or sub-step of processing the at least two temporallydefined digital images so that the particle is distinct from thebackground of each temporally defined digital image. This step ofprocessing includes one or more of the following steps or sub-steps:histogramming, color stretching, filtering, background subtraction,identifying contrast differences. The step of determining the velocityof at least one particle in a force field further includes the step orsub-step of tracking the location of the particle through the at leasttwo temporally defined digital images by determining at least onepredicted path and the distance the particle has traveled. Other stepsor sub-steps are more fully set forth in the detailed description.

According to another aspect of the present invention, a device fordetermining one or more particle physical characteristics is alsodescribed. More specifically, the device has a force field device forsubjecting at least one particle to at least one force field, asubstantially transparent flow channel, and a computer system forgathering and analyzing data associated with the at least one particle.The force field device has, among other things, a first and second forcefield producing assembly. Each assembly has a force field producingdevice and a pole piece for concentrating the force field flux. The polepieces each have a flux concentrating portion having a curved endportion for producing a region of space having a substantially constantforce field and wherein the flux concentrating portions are displacedsubstantially opposite each other with an inter-polar air gaptherebetween. The substantially transparent flow channel is positionedat least partially within the region of space and provides for theintroduction of at least one particle thereinto. A flow system having apump for controlling flow into the channel is also provided.

According to another aspect of the present invention, a system fordetermining one or more particle physical characteristics is provided.The system has a force field device for generating at least one forcefield having a predetermined force field magnitude and direction and forsubjecting at least one particle to the at least one force field, a flowsystem for regulating the introduction of the at least one particle intothe force field device, and a computer system for gathering andanalyzing data associated with the at least one particle. The computersystem has, among other things, a digital image system for acquiring atleast two temporally defined digital images of the at least oneparticle, logic for identifying and locating the at least one particleand its coordinates within the at least two temporally defined images,logic for determining the velocity of the at least one particle withinthe force field, and logic for determining at least one particlephysical characteristic from the determined velocity and thepredetermined force field magnitude and direction.

According to yet another aspect of the present invention, a pole pieceassembly for producing a region of space having a substantially constantmagnetic force field is provided. The assembly has, among other things,a first pole piece having a substantially curved flux concentratingportion, a second pole piece having a substantially curved fluxconcentrating portion, and a device for producing a magnetic flux influx communication with the first and second pole pieces. The first andsecond pole pieces are configured to form an inter-polar air gap. Thesubstantially curved flux portions of the first and second pole pieceseach have a first distal end having a curved portion and a second distalend having a curved portion. The curved portion of the each first distalend includes a predetermined radius and the curved portion of the eachsecond distal end includes an approximately hyperbolic function, whereinthe hyperbolic function is defined by the function y(x)=9.544/x²-12.719, where x and y are Cartesian coordinates (preferably inmillimeters) with the origin placed at the intersection of the plane ofsymmetry separating the pole pieces and a plane tangent to the radialportion of the distal ends of the pole pieces.

It is, therefore, an advantage of the present invention to provide ananalytical tool for analyzing and measuring at least one of a pluralityof particle characteristics.

It is another advantage of the present invention to provide a region ofsubstantially constant magnetic force for application to at least onemagnetically susceptible particle.

It is another advantage of the present invention to provide a computersystem having logic for analyzing and measuring the magneticsusceptibility of at least one magnetically susceptible particle.

Further advantages will become apparent from a consideration of theensuing description and drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

In the accompanying drawings which are incorporated in and constitute apart of the specification, embodiments of the invention are illustrated,which, together with a general description of the invention given above,and the detailed description given below, serve to example theprinciples of this invention.

FIG. 1 is a high-level functional block diagram of a quantitativeanalysis device 100 of the present invention;

FIG. 2 is a high-level flowchart of the overall Particle TrackingVelocimetry Analysis logic;

FIG. 3 is a flow chart illustrating the image processing logic of thepresent invention;

FIG. 4 is a diagram of the two-dimensional cell tracking function of thepresent invention;

FIG. 5 is a top plan view of one embodiment of a force field device ofthe present invention;

FIG. 6 is a cross-sectional view taken on section line 6--6 of FIG. 5 ofthe force field device of the present invention;

FIG. 7A is a graph showing the magnetic field lines generated by thepresent invention;

FIG. 7B is a magnified view of a portion of the force field device ofFIG. 6;

FIG. 8 is a graph illustrating the magnetic force and rate of change ofmagnetic force versus y-axis position of the force field device of FIGS.5, 6, and 7;

FIG. 9A is a graph showing the distribution of average cell diameters oflymphocyte cells as determined by the present invention and asdetermined experimentally via a Coulter Multisizer II;

FIG. 9B is a graph showing the distribution of magnetic susceptibilityof lymphocyte cells as determined by the present invention.

DETAILED DESCRIPTION OF ILLUSTRATED EMBODIMENT

Referring now to FIG. 1, a high-level functional block diagram of aquantitative analysis device 100 of the present invention is shown. Thedevice 100 has a force field device 102, digital or analog camera 104,computer system 106, input device(s) 118, and output device(s) 116. Thecomputer system 106 contains a CPU 108, memory 110, Cell TrackingVelocimetry analysis logic 112 (hereinafter CTV logic 112), video board114, and various other support devices including, for example, floppy,hard, and CD-ROM drives, fax/modem, interface logic, etc. (not shown).The CPU 108 is preferably a CPU which is capable of quickly andefficiently processing large amounts of graphical information. One suchCPU is the Intel MMX® microprocessor. However, other microprocessors mayalso be employed such as, for example, the Intel Pentium® processor,Intel 80486, or other high-performance microprocessors. One suchcomputer system having the above-described features, or easilymodifiable to have the above-described features is, for example, an IBMAPTIVA® or Gateway 2000® personal computer system with an Intel MMX®microprocessor.

The video board 114 of the present invention preferably has the abilityto capture and process high resolution video and image information fromexternal devices (e.g, digital or analog cameras) or internal devices(e.g., built-in video tuner). The video board 114 preferably contains avideo processor, video memory and various interface logic forinterfacing to digital and/or analog cameras, display devices, and thecomputer system 106. One such suitable video board 114 is the P360FPower Grabber manufactured by DPIX Technologies Inc. Other highperformance video boards having similar characteristics may also beemployed. The output device(s) 116 include(s), for example, displaymonitors, printers, and external storage devices. The input device(s)118 include(s), for example, a keyboard, mouse, and voice input. Otherinput/output devices may also be employed.

The digital camera 104 preferably contains the ability to capturehigh-resolution monochrome and/or color video and still-imageinformation. A suitable digital camera is, for example, the CCD 4915camera, manufactured by Cohu Inc. of San Diego, Calif., with a 2.5× anda 6.7× magnification insert. Other cameras having similarcharacteristics may also be employed. Additionally, magnifications otherthan 2.5× or 6.7× may also be utilized, depending on the size of thecells or particles being analyzed and the required magnification. In thealternative, a high-resolution video storage device 120 such as, forexample, a sVHS video recorder or optical disk(s) may be employed tostore the video and images for subsequent analysis and archiving.Additionally, a light source 124 may be employed to improve imagequality. The light source 124 may be a source coherent light of one ormore wavelengths such as, for example laser light, or non-coherent lightof one or more wavelengths such as, for example, white light, coloredlight, ultra-violet light, or infra-red light, or combinations thereof

The force field device 102 is responsible for a number of importantfunctions within the present invention. Firstly, the force field device102 allows the cells or particles to be subjected to and displaced by aforce field. Secondly, the force field device 102 allows for the cell orparticle displacement to be viewed and/or captured by the digital camera104. Thirdly, the force field device 102 may, in certain embodiments,provide the force field being applied (e.g., a magnetic field). Otherfunctions will also be apparent from the detailed discussion presentedbelow.

Particle Tracking Velocimetry Analysis Logic

The CTV logic 112 of the present invention analyzes a plurality ofclosely-timed cell or particle images to determine, among other things,individual cell or particle locations and velocities through eachcaptured image. All the data collected and determined by the CTV logic,including the captured image information, is preferably stored in adatabase for subsequent viewing, analysis, or review. As will bedescribed in more detail, once the cell locations and velocities areknown, many other characteristics such as, for example, cellacceleration, force, and mass may be determined therefrom. It shouldalso be noted that the CTV logic 112 is not dependent upon the specifictype of force field applied to the cells or particles. Therefore, theCTV logic may be employed in systems where the force field device isemploying magnetic, electric, or gravitational fields. The presentdiscussion will hereinafter focus on the analysis of cells; however, itshould be noted that the discussion is equally applicable to otherparticles such as, for example, cell organelles, and othermetallic/non-metallic particles.

Referring now to FIG. 2, a flow chart 200 of the overall CTV logic 112is shown. The CTV logic begins in step 202 where the digital camera 104(shown in FIG. 1) acquires a number of images. Firstly, the digitalcamera 104 acquires at least one background image. A background image isan image of the observation area of the force field device 102 whichtypically contains a glass tube or channel through which cells are orwill be visible. The background image is used in a backgroundsubtraction function of the image processing logic. See the textassociated with FIG. 3 for a detailed discussion of the backgroundsubtraction function. Secondly, the digital camera 104 acquires aplurality of closely timed digital images of the cells. Each digitalimage is acquired at an image sampling rate generally in the range of 15to 60 Hz, with a preferable image sampling rate of 30 Hz. These digitalimages are also known as, and commonly referred to as, an image "frame"or "frames." The video board 114 converts each pixel of each image frameinto one of a plurality of digital image formats which convey pixelbrightness and/or color information. The digital formats range from 8 to24 bits of information per pixel. The preferred image format is 8 bitsof gray-level information per pixel. The 8 bits of gray-levelinformation provide a range of gray-level values from 0 (i.e., black) to255 (i.e., white).

Each image frame contains a high-resolution pixel array, preferably inthe general range of 600×400 to 1280×1024 pixels. The digital cameral ofthe illustrated embodiment provides a high-resolution 624×450 pixelarray. Moreover, the digital image sampling rate of 30 Hz may beincreased or decreased depending on the required image frame resolution.For example, the sampling rate of 30 Hz produces 30 image frames persecond. If a higher image frame resolution is required, the samplingrate may be increased to, for example, 60 Hz (i.e., 60 image frames persecond.) Similarly, if a slower image frame resolution is acceptable,the sampling rate may be decreased to, for example, 15 Hz (i.e., 15image frames per second.) After the image frames are acquired in step202, the CTV logic advances to step 204 where the image frames areprocessed for standardization which facilitates the tasks of locatingand identifying individual cells and determining their velocities.

Referring now to FIG. 3, a flow chart 300 illustrating the imageprocessing logic of the present invention is shown. Generally, theacquired physical images from the digital camera 104 are not optimal forcell tracking because the gray-level differences between the backgroundimage and the cell image(s) are not distinct. Accordingly, some degreeof image processing is required. The task of locating and identifyingcells and their velocities is facilitated by processing the image framesso that they contain only bright cell images and a dark backgroundimage, and it is a primary function of the image processing logic toachieve this result, or very near thereto. To this end, the imageprocessing logic executes a plurality of steps including, but notlimited to, for example, histogramming, stretching, spatial filtering,background subtraction, pattern filtering, and pixel size matching.

Accordingly, the image processing logic starts in step 302 where ahistogramming function is executed for each image frame. Histogrammingis a statistic measure of the frequency of the gray-level versus thegray-level itself. The range of gray-level is from 0 (i.e., black) to255 (i.e., white) for an 8-bit gray-level image. Therefore, byhistogramming the gray-levels of an image frame, a range of dominantgray-levels may be determined from the frequency of their occurrence.The range of dominant gray-levels, in turn, indicate whether the cellimage is distinct from the background image of the image frame. Forexample, if the range of dominant gray-levels fall between 175 and 250,it can be said that the cell image is not distinct from the backgroundimage. However, if the range of dominant gray-levels comprises twosub-ranges with one sub-range localized near the gray-level of 0 (ie.,black), for example, and the other sub-range localized near thegray-level of 255 (i.e., white), for example, then it can be said thatthe cell image is distinct from the background image of the image frame.It should be noted that whether the cell image is distinct from thebackground image is a matter of degree. In an ideal image frame, thecell image would appear white in color (i.e., gray-level 255) and thebackground image would appear black in color (ie., gray-level 0). It isa goal of the image processing logic to standardize all image frames asclose as possible to this norm.

After step 302, the image processing logic advances to step 304 where astretching function is executed for each image frame. The stretchingfunction is employed when the distribution of the gray-level in theimage frame does not cover the fall brightness range and produces poorcontrast between the cells and the background. The stretching functionis accomplished by setting a minimum and a maximum gray-level value. Theminimum gray-level value is set to the low-end and the maximumgray-level value is set to the high-end of the general range of dominantgray-level values as determined by the histogramming function. In thestretching function, all image frame pixels with a gray-level value lessthan the minimum gray-level value are set to 0 (i.e., black). All imageframe pixels with a gray-level value greater than the maximum gray-levelvalue are set to 255 (i.e., white). All image frame pixels withgray-level values in the range between the minimum and maximum arestretched proportionally, to a value between 0 and 255, based on theiroriginal gray-level value. The result of the stretching function is animage frame that contains distributions of gray-level values whichdistinctly correspond to the cell images and the background image. Afterstep 304, the image processing logic advances to step 306.

In step 306, the image processing logic executes a low-pass spatialfiltering function for each image frame. The low-pass spatial filteringfunction removes small details, or noise, from the image frame. Low-passspatial filtering is also known as "neighborhood averaging" and is usedto reduce noise by smoothing local gray-levels of the image. After step306, the image processing logic advances to step 308.

Since the CTV logic requires image frames which contain only bright cellimages and a dark background image, a background subtraction function isexecuted for each image in step 308. The background subtraction functionis particularly useful because most experimental systems includeextraneous matter such as, for example, dirt on the surfaces of cameralenses and other observation devices such as, for example, glass tubesor channels. In the background subtraction function, an image frame ofthe background is subtracted from the image frame containing the cellimages and the background image. To recall, one of the first imagesacquired in step 202 of FIG. 2 is an image of the background of thescene where the cells will eventually appear. That is, the backgroundimage is an image of the observation area of the force field devicewhich typically contains a glass tube or channel through which cellswill be visible. Accordingly, after the background subtraction functionin step 308 is performed, each image frame generally contains brightcell images and a dark background image.

After step 308, the image processing logic proceeds to step 310 where acell template function is applied to each cell of each image frame. Acell template is a standard complete cell image which has beenpre-defined based on an actual physical image of the cell. The need toapply the cell template function arises because, after image processing,the cell images may appear as hollow spheres with their interiors havingthe same gray-level as the background image. Consequently, afterapplication of the cell template function, the cell images no longerappear as hollow spheres but as solid bright spheres. It should be notedthat application of the cell template function may be optional becauseafter image processing, some cell images may already appear as solidbright spheres. Therefore, in such cases there would be no need to applythe cell template function.

Referring now once again to FIG. 2, after the image processing of step204 has been completed, the CTV logic advances to step 206. In step 206,two-dimensional cell identification and location is performed for eachimage frame. This step involves the separation of cell images from thebackground image and the determination of cell location within the imageframe. Cell locations are identified based on the contrast differencebetween the cell image and the background image. The cell image isdefined as a shape connected set of pixels having an intensity greaterthan a given threshold gray-level value. The threshold gray-level valuecan fall within a range of possible values such as, for example, 0 (ie.,black) to 79. Therefore, in the given example, all pixels having agray-level value greater than 79 would have an intensity greater thanthe given range of threshold gray-level values and would, therefore, beinterpreted as belonging to a cell image. This result is achieved byscanning the pixels of each image frame and determining whether theirintensity is greater than the threshold value.

Once the cell images have been identified, the CTV logic determines thelocation of the center of each cell within each image frame. Thisprocess is facilitated by using the pixel array of each image frame as acoordinate system. Additionally, since each cell image is a solidsphere, or very nearly thereto, the center of the cell image is easilydetermined by locating the center of the sphere, which appears as acircle in two-dimensions. These locations are stored in a database foruse in the two dimensional cell tracking function of step 208.Additionally, the CTV logic may include a function which allows for theentry of minimum and maximum cell size and aspect ratio data as acriteria for further cell image recognition.

In step 208, the CTV logic executes the two-dimensional cell trackingfunction. This function employs a sequence of five image frames toestablish, therefrom, the most probable path (as a function of time)taken by each cell. The most probable path determination is based on theconcept of "path coherence." Generally, the concept of "path coherence"holds that cell position, velocity, acceleration, change ofacceleration, etc., are internally self-consistent and that thesecharacteristics can be described by mathematical functions that aresmooth.

The two-dimensional cell tracking function of step 208 will now bedescribed with reference to FIG. 4. Illustrated in FIG. 4 are thepositions of a single cell as determined from three consecutive imageframes. The position of the cell in the first image frame is indicatedby C1, in the second image frame by C2, and in the third image frame byC3. Starting with the cell C1 in the first frame, a search radius "r" isestablished, thereby establishing search area 402, and will be used foridentification of cell images in the second image frame. The value ofthe search radius "r" is dependent on a number of factors including, forexample, image sampling frequency and cell displacement between imageframes. Therefore, if the cell displacement between image frames isrelatively small, a small search radius "r" can be used. For example,"r" can be somewhere in the general range of 1 to 3 times the celldiameter. The ascertained cell diameter is preferably in the range of 1μm or greater. However, if the cell displacement between image frames isrelatively large, a larger search radius "r" would be required (e.g.,greater than the general range of 1 to 3 times the cell diameter). Thesame search radius "r" is established for every cell of an image frame.

Accordingly, once the search radius "r" has been established in thefirst image frame, all cells in the second image frame within the searchradius are tagged and identified. As shown in FIG. 4, cell image C2 iswithin the search radius and search area 402. Since the coordinates ofthe center of cell image C2 are known, the distance D1 and vectordirection from cell image C1 can be determined. These values are used todetermine a candidate path 404 for the cell. Therefore, from the firstand second image frame, the path and location of the cell in the thirdframe is predicted (shown at point "P" on predicted path 404). Oncepredicted, the path and location of the cell is compared to the actualposition of the cell image C3 in the third frame. After comparison, theerror between the predicted (i.e., point "P") and actual cell imageposition C3 is determined and added to a penalty function. The penaltyfunction is a measure of path coherence. That is, the smaller thepenalty function, the greater the path coherence. Therefore, the errorbetween cell images C1 and C2 is zero by default since at least 2 pointsare required for a path. However, an error may exist, as shown in FIG.4, between the predicted third image frame cell location (i.e., point"P" on predicted path 404) and the actual third image frame celllocation C3. Since the coordinates for the predicted cell location "P"and the actual cell location C3 are known, an error value may bedetermined therefrom.

This procedure is repeated with the fourth image frame using the dataacquired from the first three image frames and, similarly, for the fifthimage frame using the data acquired from the first four image frames. Asmay be the case, the CTV logic may have to analyze several possiblepaths if more than one cell image has been tagged and identified withina search radius. In such situations, the values of the penalty functionsfor each separate possible path are compared and the path with thesmallest penalty function value is chosen as the correct path. Once theimage frames have been analyzed sequentially from the first image frameto the fifth image frame, the process is reversed and the image framesare analyzed sequentially starting with the fifth image frame to thefirst image frame. This allows for the consideration of any biases whichmay be caused by the order of image frame analysis.

Specifically, the bias value is a measure of reliability that adetermined cell path is the correct cell path. For example, if drasticdifferences between the forward analysis penalty function value and thereverse analysis penalty function value are present, a large bias in oneof the two directions of analysis exists--thereby indicating that thepresently determined cell path may be less reliable than other potentialcandidate cell paths. Similarly, a small bias value would indicate thatthe presently determined cell path is more reliable than other potentialcandidate cell paths. Accordingly, cell paths having small penaltyfunction values and small, or no, bias values are reliable as determinedor most probable cell paths.

Hence, by knowing the location of each cell from image frame to imageframe and the time between image frames (ie., sampling frequency), anumber of cell characteristics can be determined by the CTV logic 112such as, for example, the velocity of the cell from image frame to imageframe. Furthermore, since the velocity of the cell is known at aplurality of different times, the acceleration of the cell can also bedetermined. Still further, if the mass of the cell is known, the forceacting on the cell can be determined or vice-versa. Therefore, the CTVlogic of the present invention can determine a wide range of physicalparameters including, for example, all of the above-mentioned parametersand values. Additionally, depending on the type of force field device102 being employed, particle physical characteristics such as, forexample, magnetic susceptibility, charge cell separation and size, maybe determined from the above physical parameters and values. For all ofthe data collected, the CTV logic 112 can determine an average value,the standard deviation, and the range for the cell population analyzedthrough a plurality of known means. These values are the ultimateoutputs of the CTV logic 112 and may be output to a display monitor,printer, or storage device.

Force Field Device

As already mentioned, the force field device 102 (shown in FIG. 1)provides a number of important functions within the present inventionsuch as, for example, allowing the cells to be subjected to anddisplaced by a force field and allowing for cell displacement to beviewed and/or captured by a camera. The force field device 102 of thepresent invention may employ any one of a variety of force fieldsincluding, for example, flow, magnetic, electric, and gravitationalfields. One illustrated embodiment of a force field device 102 employinga magnetic field is shown in FIGS. 5, 6, 7A, and 7B. Through the use ofa magnetic field, the present invention can determine, for example, themagnetic susceptibility of cells. Once determined, the magneticsusceptibility can be used to appropriately design magnetic field(s) andthe magnetic assemblies of cell sorting devices. This is of particularimportance for fractional cell sorting devices which sort cells based onthe density of magnetically labeled cell surface markers.

Referring now to FIGS. 5 and 6, a force field device 102 for subjectingcells to a magnetic force field is shown. FIG. 5 is a top plan view andFIG. 6 is a cross-sectional view taken on section line 6--6 of FIG. 5.Force field device 102 includes a base 606, two pairs of force fieldproducing magnets 602 and 604, and two pole pieces 502 and 504. Themagnets 602 and 604 are generally rectangular in shape and preferably inthe range of about 2"×2"×1" and preferably made from a permanentmagnetic material such as, for example, a neodymium-iron-boron alloy.The base 606 and the pole pieces 502 and 504 are preferably made from amaterial that is capable of having a magnetic flux induced therein suchas, for example, 1018 low-carbon cold-finished steel. The pole pieces502 and 504 each have a flux concentrating portion 516 and 518,respectively, and top and bottom surfaces 608 and 610, respectively. Thedistance between top and bottom surfaces 608, 610 and 612, 614, isapproximately in the range of 12-13 mm, with a preferred distance ofapproximately 12.5 mm.

The base 606, magnets 602 and 604, and pole pieces 502 and 504 areassembled as shown in FIGS. 5 and 6 so as to form an inter-polar air gap505 and utility spaces 506 and 508. If necessary, utility space 506 maybe used for placing the digital camera 104 in close proximity to theinter-polar air gap 505. Similarly, utility space 508 may be used forproviding a light source or mirror 510 which directs light through theinter-polar air gap 505. A channel 514 is positioned within theinter-polar air gap 505 such that cells therein are subjected to asubstantially uniform magnetic field. The channel 514 is made from anoptically clear inert material such as, for example, borosilicate glass.The channel 514 is substantially rectangular in cross-section.

Referring now to FIG. 7A, a graph showing the magnetic field linesversus x and y position generated by the present invention isillustrated. In particular, the location of the region of constantmagnetic force 702 is shown relative the inter-polar air gap, along withthe magnetic field lines B.

Referring now to FIG. 7B, a magnified view of portion 7 of FIG. 6 isshown. The flux concentrating portions 516 and 518 have end surfaces 704and 706. End surfaces 704 and 706 each have curved distal ends 712, 714and 716, 718, respectively. Curved distal ends 712 and 716 have a radiusin the general range of 3 mm with a preferable radius of 3.18 mm. Curveddistal ends 714 and 718 are generally hyperbolic and preferably definedby the hyperbolic function:

    y(x)=9.544/x.sup.2 -12.719

where x and y are Cartesian coordinates, preferably in millimeters, withthe origin placed at the intersection of the plane of symmetryseparating the pole pieces and a plane tangent to the radial portion ofthe distal ends of the pole pieces. In the preferred embodiment, distalends 712 and 714 are configured such that they are continuous with eachother. Distal ends 716 and 718 are also similarly configured. However,in alternate embodiments, an approximately linear surface may beprovided between distal ends 712 and 714 so as to also provide acontinuous joinder of the distal ends. Distal ends 716 and 718 may alsobe similarly joined by an approximately linear surface.

The channel 514 is preferably placed within the inter-polar air gap 505such that it is very nearly in physical contact with the end surfaces704 and 706. Alternatively, the channel 514 may be placed in actualphysical contact with end surfaces 704 and 706. The width of theinter-polar air gap 505 is, at its narrowest, approximately 2 mm. Soconfigured, the force field device 104 generates a region 702 ofsubstantially constant magnetic force which is exerted onto the cellspresent within this region. The gradient of the magnetic field energy(∇(B² /2 μ₀)) is generally illustrated at 708 and the constant magneticenergy lines (B² /2 μ₀) are generally illustrated at 710.

Referring now to FIG. 8, a first graph 804 illustrating the magneticenergy B² /2 μ₀ versus y-axis position (at x=0) of the force fielddevice of FIGS. 5, 6, 7A and 7B is shown and a second graph 802illustrating the rate of change of the magnetic energy B² /2 μ₀ withrespect to the y-axis position at x=0 (i.e., the derivative dB² /dy) isalso shown. The region 702 of FIG. 7B is generally indicated in FIG. 8and falls within the general range of -7.5 to -9.5 mm from the top ofthe pole pieces 502 and 504. It should be noted that changes in polepiece geometry will affect the y-axis position of the substantiallyconstant magnetic force region 702.

The force field device 102 of the present invention is in fluidcommunication with a flow system 122 (shown in FIG. 1) which providesfor the injection of cells and a carrier medium into the channel 514 andthe flow field. The flow system preferably contains a disposableinjection syringe pump which is in fluid communication with the channel514 via silicone tubing. The other end of the channel 514 is in flowcommunication with a waste vessel also via silicone tubing. In thealternative, the inlet portion of channel 514 may be in fluidcommunication with an injection device such as, for example, adisposable syringe pump, and the exit portion of the channel 514 may befluid communication with an aspirating device such as, for example, anaspirating syringe pump. The flow rate generated by the two pumps beingcontrolled by the computer system 106 or other control logic within thepumps.

As mentioned above, the present invention may be used to determine aplurality of cell characteristics including, for example, cell size andmagnetic susceptibility. The following discussion will now focus onthese two examples:

Determination of Cell Size based on Cell Settling Velocities

For a spherical particle settling at terminal velocity, it can be shownfrom Stokes' law that the diameter of the spherical particle D_(c) isrelated to the its velocity V_(c) by the following equation (1):##EQU1## where η is equal to the viscosity of the fluid, ρ_(c) is thedensity of the cell, ρ is the density of the fluid and g is 9.8 m/s² forgravity. Hence, the present invention can be used to determine data fromwhich equation (1) can be solved for the cell diameter D_(c).

More specifically, the CTV logic analyzes captured images of cells whichare subjected to only a gravitational force field (as opposed to anelectric or magnetic force field) and determines the cell settlingvelocities therefrom. Once the cell settling velocities V_(c) are known,along with the other values of Equation (1), the diameter of the cellD_(c) is determined. Illustrated in FIG. 9A is a graph showing thedistribution of cell diameters of lymphocyte cells as determined by thepresent invention (i.e., solid line) and as determined experimentallyvia a commercial cell sizing device (i.e., a Coulter Multisizer II). TheCoulter Multisizer II was used to determine cell diameter D_(c). Itshould be noted that the primary peak and shoulder generated by eachmethod are in close agreement with each other. The large peak around20×10⁻⁶ m corresponds to clumps of cells which can be observed visually.The CTV logic of the present invention can also be modified to rejectanomalies such as, for example, unreliable or erroneous data.

Determination of Magnetic Susceptibility based on Cell Velocities

The concept of sorting materials based on their magnetic responsivenesswas first introduced in the industrial and mining arts. These methodsrelied on the intrinsic magnetic properties of the sorted material(generally, iron (i.e., magnetic) from non-iron arts (i.e.,non-magnetic)) as a basis of operation. See U.S. Pat. No. 2,056,426issued to Frantz, "Magnetic Separation Method and Means," in 1936.However, most cells are not intrinsically magnetic or paramagnetic. Toovercome this deficiency, magnetic antibodies have been developed whichrender cells paramagnetic. Accordingly, the ability to separate a cellbased on magnetic forces is dependent on the ability to impart onto thecell a paramagnetic label.

A cellular labeling complex generally contains a cell having a surfaceantigen or marker, e.g., protein(s), which serve as a marker to which amagnetic antibody can be attached. Other cellular labeling complexes arealso possible. For example, one may attach a fluorescent label whichincludes a primary antibody--fluorescein conjugate to a surface markerand a secondary antibody--magnetic label conjugate to the primaryantibody. The primary advantages of this type of cellular labelingcomplex is that it allows for additional analysis by FACS(Fluorescence-Activated Cell Sorting) systems and the analysis of cellmotion using ultra-violet light. Other suitable labeling complexesinclude, for example, high or low density labels (e.g., high densitymetal particles such as gold, or low density particles such as polymericparticles), electrically-charged labels (e.g., ions) or combinations ofall of the aforementioned types of labels. Consequently, once ahomogeneous cell population has been paramagnetically labeled, it may beseparated from a heterogeneous cell population.

The magnetic antibody may be of a plurality of types. More particularly,magnetic antibodies can be classified into three broad categories whichare based on size: Particulate labels, Colloidal magnetic labels andMolecular magnetic labels. Particulate labels are the largest inrelative size to the other labels and Molecular magnetic labels are thesmallest in terms of relative size. Additionally, cells may be renderedparamagnetic by binding a specific paramagnetic compound to a specifichapten on a cell or the specific or non-specific binding of aparamagnetic metal or metal complex directly to a cell (i.e., metalbinding microorganism or by phagocytosis). Therefore, it should beapparent to those skilled in the art that a cell may be renderedparamagnetic by a number of ways. While under the proper designspecifications any of the three types of magnetic labels can besuitable, the present invention preferably employs either colloidalmagnetic labels or molecular magnetic labels.

As mentioned, once a homogeneous cell population has beenparamagnetically labeled, it may be separated from othernon-paramagnetic cell populations within a heterogeneous cellpopulation. The separation of paramagnetic cells from non-paramagneticcells is commonly referred to as binary separation. However, because thedegree to which a paramagnetic label binds to a cell (i.e., magneticsusceptibility) may vary significantly within a given heterogeneous cellpopulation, and sometimes even within a homogeneous cell population, theopportunity to fractionally sort the paramagnetically labeled cellpopulation into paramagnetic sub-populations has arisen. Accordingly,knowledge of the average magnetic susceptibility of a homogeneous cellpopulation, along with the standard deviation and range, is required inthe design of such fractional cell sorting devices.

In particular, it can be shown that the magnetic susceptibility Δ.sub.χof a labeled cell migrating in a magnetic field is given by equation(2): ##EQU2## where μ₀ is permeability of free space, V_(c) is velocityof the cell, D_(c) is cell diameter, α is cell surface marker density, βis number of magnetic labels bound per cell surface receptor site, and Bis the magnetic flux density. Equation (2) can be solved for the eitherthe magnetic susceptibility Δ.sub.χ or the cell surface marker density αthrough the proper use of controls and independently determined valuesfor the other variables.

Specifically, as described above, the CTV logic is capable ofdetermining the velocity of the cell V_(c) =ν_(y) and the cell diameterD_(c). Additionally, since the force field device 102 of the presentinvention provides a substantially uniform magnetic force within aportion of the air gap, the ##EQU3## term in the denominator of Equation(2) is represented by a constant. Given all the known variables, themagnetic susceptibility Δ.sub.χ may be determined. Illustrated in FIG.9B is a graph showing the distribution of magnetic susceptibilityΔ.sub.χ of CD4 labeled lymphocytes which was generated by the presentinvention.

As described above, the present invention may alternatively employ cellswhich have been labeled with differential density labels such as, forexample, high density (e.g., gold) and low density (e.g., polymericparticles) labels. Similar to paramagnetic labeling, density labeling ofcells modifies the cell motion in response to the various force fields(e.g., gravitational field) which can be employed by the presentinvention. Alternatively, electrically-charged labels such as, forexample, ions, can also be employed by the present invention. Similar toparamagnetic labeling and density labeling, electrically-chargedlabeling of cells also modifies the cell motion in response to thevarious force fields (e.g., electric field) which can be employed by thepresent invention. Moreover, combinations of paramagnetic, density, andelectrically charged labeling may be employed to further class andsub-class particular cell populations of interest based on the presenceor absence of particular labels. Once the motion of labeled cells hasbeen analyzed to determine, for example, their velocity, othercharacteristics such as mass, acceleration, density, phagocytic capacityof negatively charged cells, etc., can be determined therefrom.

It should also be mentioned that a fluorescent label such as, forexample, fluorochrome, may be additionally employed to class andsub-class cell populations of interest based on the presence or absenceof one or more fluorescent labels. Light sources which are compatiblewith fluorescent labels include, for example, ultra-violet and visiblelight sources. The fluorescent labels preferably emit or transmit colorsin the range of green, yellow, or red. Once labeled, the cells can beclassed or sub-classed based on fluorescence.

While the present invention has been illustrated by the description ofembodiments thereof, and while the embodiments have been described inconsiderable detail, it is not the intention of application to restrictor in any way limit the scope of the appended claims to such detail.Additional advantages and modifications will readily appear to thoseskilled in the art. For example, it is possible to stain cells with afluorescent label and then use a laser for illumination. This wouldinvolve the use of specific instruments to detect the light emitted fromthe fluorescent labels. Moreover, the present invention can be utilizedwith any technique which allows for the classification of particlesbased the particles' behavior in the presence of a force field and/orelectromagnetic energy. Therefore, the invention, in its broaderaspects, is not limited to the specific details, the representativeapparatus, and illustrative examples shown and described. Accordingly,departures may be made from such details without departing from thespirit or scope of the applicant's general inventive concept.

We claim:
 1. A method of quantifying at least one of a plurality ofparticle physical characteristics, the method comprising the stepsof:(a) generating a region of space having a substantially constantforce field; (b) determining the velocity of at least one particlewithin the region by:(1) identifying and locating the particle and itscoordinates in at least two temporally defined digital images, and (2)processing the at least two temporally defined digital images so thatthe particle is distinct from the background of each temporally defineddigital image, wherein the step of processing comprises the step ofhistogramming each temporally defined digital image by determining thecolor level frequency versus the color level; and (c) determining the atleast one of a plurality of particle physical characteristics from:(1)the determined velocity; and (2) a predetermined force field magnitudeand direction.
 2. The method of claim 1 wherein the step ofhistogramming further comprises the step of determining a range ofdominant color levels.
 3. The method of claim 2 wherein the step ofprocessing further comprises the step of stretching all color levels inthe range of dominant color levels.
 4. The method of claim 3 wherein thestep of processing further comprises the step of low-pass spatialfiltering each temporally defined digital image.
 5. The method of claim4 wherein the step of processing further comprises the step of executinga background subtraction function for each temporally defined digitalimage.
 6. The method of claim 5 wherein the step of identifying andlocating the particle and its coordinates comprises the step ofsearching for contrast differences in each temporally defined digitalimage.
 7. The method of claim 1 wherein the step of processing furthercomprises the step of setting all color levels below a predeterminedcolor level to a low-end color level.
 8. The method of claim 1 whereinthe step of processing further comprises the step of setting all colorlevels above a predetermined color level to a high-end color level. 9.The method of claim 1 wherein the step of identifying and locating theparticle and its coordinates comprises the step of searching forcontrast differences in each temporally defined digital image.
 10. Themethod of claim 1 wherein the step of determining the at least one of aplurality of particle physical characteristics from the determinedvelocity comprises the step of determining a particle physicalcharacteristic selected from the group consisting of particle size,shape, magnetic susceptibility, magnetic label density, chargeseparation, and dielectric constant.
 11. The method of claim 1 furthercomprising the step of placing at least one particle in a force field.12. The method of claim 11 wherein the step of placing at least oneparticle in a force field comprises the step of placing the at least oneparticle in a flow stream.
 13. The method of claim 11 wherein the stepof placing at least one particle in a force field comprises the step ofplacing the at least one particle in a force field selected from thegroup consisting of flow, gravitational, magnetic, and electricalfields.
 14. The method of claim 1 further comprising the step ofmagnetically labeling the at least one particle and wherein step (b)further comprises the step of determining the magnetic susceptibility ofthe at least one particle.
 15. The method of claim 1 further comprisingthe step of magnetically labeling the at least one particle and whereinstep (b) further comprises the step of determining the surface labeldensity of the at least one particle.
 16. The method of claim 1 whereinstep (b) further comprises the step of determining the particlediameter.
 17. The method of claim 1 further comprising the step oflabeling the at least one particle with a fluorescent label and step (b)further comprises the step of selectively determining the velocity ofthe at least one cell within the region by identifying and locating theat least one cell and its coordinates in at least two temporally defineddigital images.
 18. The method of claim 1 further comprising the step oflabeling the at least one particle which a density label and step (b)further comprises the step of selectively determining the velocity ofthe at least one cell within the region by identifying and locating theat least one cell and its coordinates in at least two temporally defineddigital images.
 19. The method of claim 1 further comprising the step oflabeling the at least one particle which an electrically-charged labeland step (b) further comprises the step of selectively determining thevelocity of the at least one cell within the region by identifying andlocating the at least one cell and its coordinates in at least twotemporally defined digital images.
 20. The method of claim 1 furthercomprising the step of labeling the at least one particle with acombination of one or more magnetic, fluorescent, density, andelectrically-charged labels and step (b) further comprises the step ofselectively determining the velocity of the at least one cell within theregion by identifying and locating the at least one cell and itscoordinates in at least two temporally defined digital images.
 21. Themethod of claim 20 wherein step (b) further comprises the step ofselectively determining at least one cell characteristic selected from agroup consisting of: phagocytic capacity of negatively charged cells,and cell surface charge density.
 22. The method of claim 1 furthercomprising the step of generating a region of space having asubstantially constant force field comprises the step of generating aregion of space having a substantially constant force field forpredetermined time period.
 23. The method of claim 1 wherein the step ofgenerating a region of space having a substantially constant force fieldcomprises the step of generating a force field which is substantiallyorthogonal to a gravitational field and wherein the force field isselected from the group consisting of: flow, magnetic, electric, andelectromagnetic fields.
 24. The method of claim 1 wherein the particleis selected from a group consisting of: cells, cell organelles,platelets, inorganic, organic, biological, and polymeric particles whichare optically visible.
 25. A method of quantifying at least one of aplurality of particle physical characteristics, the method comprisingthe steps of:(a) generating a region of space having a substantiallyconstant force field; (b) determining the velocity of at least oneparticle within the region by identifying and locating the particle andits coordinates in at least two temporally defined digital images; and(c) determining the at least one of a plurality of particle physicalcharacteristics from:(1) the determined velocity; (2) a predeterminedforce field magnitude and direction; and (3) tracking the location ofthe particle through the at least two temporally defined digital imagesby determining at least one predicted path.
 26. The method of claim 25wherein the step of tracking the location of the particle through the atleast two temporally defined digital images comprises the step ofestablishing a search radius around the particle in each digital imageand searching the search radius in each adjacent digital image toidentify any particles which are at least partially within the radius.27. The method of claim 26 wherein the step of determining the velocityof at least one particle in a force field further comprises the step ofdetermining a penalty function value for each predicted path.
 28. Themethod of claim 27 wherein the step of determining the velocity of atleast one particle in a force field further comprises the step ofcomparing the penalty function for each predicted path and selecting thepredicted path with the lowest penalty function as the actual path ofthe particle.
 29. The method of claim 28 wherein the step of determiningthe velocity of at least one particle in a force field further comprisesthe step of determining the distance the particle has traveled based onthe particle locations in the selected actual path of the particle ineach temporally defined digital image.